Dr. Angela Schwering

Whereas symbol-based systems, like deductive reasoning devices,
knowledge bases, planning systems, or tools for solving constraint
satisfaction problems, presuppose (more or less) the consistency of data
and the consistency of results of internal computations, this is far
from being plausible in real world applications, in particular, if we
take natural agents into account. Furthermore in complex cognitive
systems, that often contain a large number of different modules,
inconsistencies can jeopardize the integrity of the whole
system.

This
paper addresses the problem of resolving inconsistencies in hybrid
cognitively inspired systems on both levels, in single processing
modules and in the overall system. We propose the hybrid architecture
I-Cog as a flexible tool, that is explicitly designed to reorganize
knowledge constantly and use occurring inconsistencies as a nonclassical
learning mechanism.

Although there is quite a long tradition of research in analogies, there
aren’t many formal and algorithmic theories of analogical reasoning yet.
Her project tries to close this gap by providing a mathematical or
rather formal base for analogies, analogical reasoning, and related
phenomena (like analogical learning, metaphors).

As a method, heuristic
driven theory projection will be used, an approach that algorithmically
produces a generalized theory for given source and target domains. The
focus of research is located at the formal properties of theory
projection and the development of a formal semantics for analogies. The
practical aims are the modeling of predictive analogies and analogical
learning. The essential contributions to current research that can be
expected from this project are formalisms for the representation of
analogies as well as proposals for a denotational semantics of analogies
which allow a new perspective on this area. Furthermore, new and
efficient algorithms for analogical reasoning will be developed, which
allow us to test the theory on practical applications. Last but not
least,
her project will contribute to the conceptual analysis of analogies.